基于聚类算法的客户细分

Sharanjit Kaur, Sarabjeet
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引用次数: 1

摘要

在过去的几年里,数据挖掘和机器学习技术被频繁地用于获得预测和回答可能从数据中产生的许多问题。本文介绍了客户细分的方法。作为指导企业进行更有效的营销和产品开发的工具,客户细分几乎具有无限的潜力。本文讨论的客户细分方法是基于聚类算法的。为了可视化数据和生成的集群,还使用了可视化工具。最后,考虑了一种可以处理混合类型的多个相关测度的通用潜在类模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Customer Segmentation Using Clustering Algorithm
In the past years, data mining and machine learning techniques are getting used frequently to obtain predictions and to answer as many questions that may arise from the data. In this paper, customer segmentation approach is described. Customer segmentation has nearly limitless potential as a tool for guiding businesses toward more effective marketing and product development. The methods discussed in this article for customer segmentation is based on clustering algorithms. In order to visualize data and the resulting cluster a visualization tool is also used. Finally, a general latent class model is considered that can handle multiple dependent measures of mixed type.
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